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ISSN (Online): 2349-7084

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INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING IN RESEARCH TRENDS

VOLUME 1, ISSUE 6, DECEMBER 2014, PP 405-408

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Extracting Spread-Spectrum Hidden Data from Picture Representation

1 R NEELIMA DEVI , 2 B.RANJITH

1 M.Tech Research Scholar, Priyadarshini Institute of Technology and Science for Women

2 HOD-CSE, Priyadarshini Institute of Technology and Science for Women

Abstract: In this paper, we introduce a novel high bit rate LSB Picture information concealing system. The fundamental

thought of the proposed LSB computation is information installing that causes negligible implanting contortion of the host picture. Utilizing the proposed two-stage result, information concealing bits are inserted into higher LSB layers, resulting in expanded vigor against clamor expansion or picture layering. Listening tests demonstrated that the perceptual nature of information hided picture is higher on account of the proposed technique than in the standard LSB strategy.

Index Terms: Higher LSB, Guard Pixels, Stegnography,Multi- carrier, Information hiding, Data Encryption.

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I INTRODUCTION Data tracking and tampering are rapidly increasing in

everywhere like online tracking, mobile tracking etc. So

we need a secured communication scheme for

transmitting the data. For that, we are having many

data hiding schemes and extraction schemes. Data

hiding schemes are initially used in military

communication systems like encrypted message, for

finding the sender and receiver or it’s very existence.

Initially the data hiding schemes are used for the copy

write purpose. In [1] Fragile watermarks are used for

the authentication purpose, i.e. to find whether the data

has been altered or not. Likewise the data extraction

schemes also provide a good recovery of hidden data

.This is the goal of the secured communication.

Steganography is the art of covered or hidden writing.

The purpose of steganography is covert

communication to hide a message from a third party.

Steganography is often confused with cryptology

because the two are similar in the way that they both

are used to protect important information. The

difference between the two is that Steganography

involves hiding information so it appears that no

information is hidden at all. If a person or persons

views the object that the information is hidden inside

of he or she will have no idea that there is any hidden

information, therefore the person will not attempt to

decrypt the information. Steganography in the modern

day sense of the word usually refers to information or a

file that has been concealed inside a digital Picture,

Video or Image file. What Steganography essentially

does is exploit human perception; human senses are

not trained to look for files that have information

hidden inside of them. Generally, in steganography,

the actual information is not maintained in its original

format and thereby it is converted into an alternative

equivalent multimedia file like image, video or image

which in turn is being hidden within another object.

This apparent message (known as cover text in usual

terms) is sent through the network to the recipient,

where the actual message is separated from it. There

are many to embed information into a popular media

using steganography. A good example of this is the

relationship between are coded song, and its lyrics. The

image file containing the recording is much larger than

the song lyrics stored as a plain ASCII files.

In this Paper we state the fact that steganography can

be successfully implemented and used into a next

generation of computing technology with image and

video processing abilities. The LSB method used for

this project which satisfies the requirement of

steganography protocols. This research will include

implementation of steganographic algorithm for



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encoding data inside video files, as well as technique to

dynamically extract that data as original.

II RELATEDWORK

There are many data hiding and data extraction

schemes are comes into existence. The important data

hiding technique is steganography. It is differ from

cryptography in the way of data hiding. The goal of

steganography is to hide the data from a third party

whereas the goal of cryptography is to make data

unreadable by a third party. In [2] the steganalysis

method is used. The goal of steganalysis is to

determine if an image or other carrier contains an

embed message. In my project the concept of

Watermarked Content only attack‟ in the

watermarking security context is taken.i.e the blindly

recovery of data is considered. In [3],in steganalysis

concept it is said to be Universal Steganalysis means

instead of using any priori information ,they take into

account all available steganography methods to devise

a single steganalysis framework. This approach can

detect any steganography if sufficient numbers of cover

and stego images have been taken into account during

the design process. In [4] spread spectrum embedding

algorithm for blind steganography have based on the

understanding that the host signal acts as a source of

interference to the secret message of interest. Such

knowledge can be useful for the blind receiver at the

recovery side to minimize the recovery error rate for a

given host signal. To increase the security and payload

rate the embedded will take multicarrier embedding

concept. In [5] the spread spectrum communication is

explained. Here a narrow band signal is transmitted

over a much larger bandwidth such that the signal

energy present in any single frequency is

imperceptible. Similarly in SS embedding scheme, the

hidden data is spread over many samples of host signal

by adding a low energy Gaussian noise sequence. The

DCT transformation is taken for embedding purpose as

a carrier since it is a fast algorithm and for it’s efficient

implementation. In [6] the Generalized Gaussian

Distribution (GGD) has been used to model the

statistical behavior of the DCT coefficients. In [7] there

are many extraction procedures to seek the hidden

data. Built is having some disadvantages. Iterative

Least Square Estimation (ILSE) is prohibitively

complex even for moderate values. Pseudo-ILS (ILSP)

algorithm is not guaranteed to converge in general and

also it provides measurably worse results. So, these

two algorithms coupled and so called Decoupled

weighted ILSP (DW-ILSP).But here also have a

disadvantage like, it may not be valid for large N.

III. PROPOSED METHODOLOGY 3.1. Algorithms

Data Hiding:-

1. Select an Image

2. Split an Image into multi-carrier objects.

3. Select a multi-carrier image.

4. Select Secrete data for hiding.

5. Encrypt data with shifting method

6. Split data into equal number of carrier objects.

7. Apply Higher LSB Method for replacing pixels bits

with encrypted data bits by taking one multicarrier

image object & secret data segment.

8. Repeat Step 3 & Step 7 until all encrypted data

segments not hidden into multi carrier images.

9. Join multi carrier’s objects to create single

image.

10. Stop

Fig 1: Data Hiding in an Image

Data Extraction:-

1. Select a Stego Image.

2. Split stego Image.

3. Apply Higher LSB Extraction algorithm.

4. Select length Key.

5. Extract data bits from 1 to 5 LSB color pixels



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bits.

6. Generate Data.

7. Decrypt Data.

8. Stop

Fig 2. Data Extraction

IV EVALUTION The proposed method is to extract the hidden data

from the digital media. Here blindly recovery of data is

considered. That is the original host end embedding

carrier is not need to be known. This method uses

multicarrier embedding and DCT [15] transformation

for the embedding the data into the host image. The M-

IGLS algorithm is used for the extraction purpose. This

algorithm is a low complexity algorithm and it attains

the probability of error recovery equals to known host

and embedding carriers. It is used as a tool to analyze

the performance of the data hiding schemes.

Fig.3 Extracted Data

Fig. 4 Graph for PSNR verses image number

V CONCLUSION

We presented a reduced distortion algorithm for LSB

image steganography. The key idea of the algorithm is

data hiding bit embedding that causes minimal

embedding distortion of the host image. Visualization

tests showed that described algorithm succeeds in

increasing the depth of the embedding layer from 1th

to 5LSBlayer without affecting the perceptual

transparency of the data hided image signal. The

improvement in robustness in presence of additive

noise is obvious, as the proposed algorithm obtains

significantly lower bit error rates than the standard

algorithm. The steganalysis of the proposed algorithm

is more challenging as well, because there is a

significant cryptography provided for data security.

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